code: def __init__(
      self, config: GPTConfig, dtype: torch.dtype = torch.float32
  ) -> None:
      super().__init__()
      self.tok_emb = nn.Embedding(
          config.vocab_size,
          config.n_embd,
          device=config.device,
          dtype=dtype,
      )
      self.pos_emb = nn.Parameter(
          torch.zeros(
              1,
              config.block_size,
              config.n_embd,
              device=config.device,
              dtype=dtype,
          )
      )
      self.drop = nn.Dropout(config.embd_pdrop)
      self.block_size: int = config.block_size
  
imports: import math
  from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new EmbeddingStem object from inherited base classes: nn with example: obj = EmbeddingStem(config, dtype)